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27
| # /etc/modprobe.d/nvidia.conf | |
| # NVIDIA Linux modprobe.d Configuration | |
| # | |
| # Memory and Performance Enhancements: | |
| # | |
| # - NVreg_UsePageAttributeTable=1 (Default: 0) | |
| # Activates the Page Attribute Table (PAT) for improved memory management. | |
| # PAT creates a partition table at a fixed register-mapped address, potentially enhancing CPU performance. | |
| # |
| <!DOCTYPE html> | |
| <html lang="en"> | |
| <head> | |
| <meta charset="UTF-8"> | |
| <meta name="viewport" content="width=device-width, initial-scale=1.0"> | |
| <title>Bero - Software Engineer</title> | |
| <style> | |
| * { | |
| margin: 0; | |
| padding: 0; |
| # OpenClaw Implementation Prompts | |
| Each prompt below is a self-contained brief you can hand to an AI coding assistant (or use as a project spec) to build that use case from scratch. Adapt the specific services to whatever you already use — the patterns are what matter. | |
| --- | |
| ## 1) Personal CRM Intelligence | |
| ``` | |
| Build me a personal CRM system that automatically tracks everyone I interact with, with smart filtering so it only adds real people — not newsletters, bots, or cold outreach. |
| https://youtu.be/-C-JoyNuQJs?t=39m45s | |
| When I put the reference implementation onto the website I needed to | |
| put a software license on it. | |
| And I looked at all the licenses that were available, and there were a lot | |
| of them. And I decided that the one I liked the best was the MIT License, | |
| which was a notice that you would put on your source and it would say, | |
| "you're allowed to use this for any purpose you want, just leave the | |
| notice in the source and don't sue me." |
North-Holland Publishing Company
Microprocessing and Microprogramming 15 (1985) 253-261
OCR transcription from PDFs found at https://ingenieria-de-software-i.github.io/assets/bibliografia/programming-as-theory-building.pdf and https://pages.cs.wisc.edu/~remzi/Naur.pdf
Invited keynote address at Euromicro 84, 1984 August 28, Copenhagen, Denmark.
| /* | |
| * Copyright 2026 Kyriakos Georgiopoulos | |
| * | |
| * Licensed under the Apache License, Version 2.0 (the "License"); | |
| * you may not use this file except in compliance with the License. | |
| * You may obtain a copy of the License at | |
| * | |
| * http://www.apache.org/licenses/LICENSE | |
| * | |
| * Unless required by applicable law or agreed to in writing, software |
| Latency Comparison Numbers (~2012) | |
| ---------------------------------- | |
| L1 cache reference 0.5 ns | |
| Branch mispredict 5 ns | |
| L2 cache reference 7 ns 14x L1 cache | |
| Mutex lock/unlock 25 ns | |
| Main memory reference 100 ns 20x L2 cache, 200x L1 cache | |
| Compress 1K bytes with Zippy 3,000 ns 3 us | |
| Send 1K bytes over 1 Gbps network 10,000 ns 10 us | |
| Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD |
Add this file to your AI assistant's system prompt or context to help it avoid common AI writing patterns. Source: tropes.fyi by ossama.is
I managed to get top 7 via a bot trained using ppo , the model archeticture is a Unet of size 160k with the exception of using 2 down/up layers instead of 3, i had an end reward -1,0,1 for each player and a small reward if a snake lost/gained a cell.
Input height and width is the maximum height and width possible + 8 on each side to handle snakes going out of bound which is 40x60 (it was really slow to train). i then center the grid and pad all 4 size by empty space. Input size is 17 channels of size 40x60, and snakes share the same channel.